Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

implementation of central and neighbour mask for spherical expansions #420

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
24 changes: 24 additions & 0 deletions bindings/rascal/representations/spherical_expansion.py
Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,12 @@ class SphericalExpansion(BaseIO):
should contain all the species present in the structure for which
invariants will be computed

central_species : list
list of central atom species that are only computed

neighbour_species : list
list of neighbour atom species that are only computed

compute_gradients : bool
control the computation of the representation's gradients w.r.t. atomic
positions.
Expand Down Expand Up @@ -178,6 +184,8 @@ def __init__(
optimization_args=None,
expansion_by_species_method="environment wise",
global_species=None,
central_species=None,
neighbour_species=None,
compute_gradients=False,
cutoff_function_parameters=dict(),
):
Expand All @@ -195,11 +203,23 @@ class documentation
elif not isinstance(global_species, list):
global_species = list(global_species)

if neighbour_species is None:
neighbour_species = []
elif not isinstance(neighbour_species, list):
neighbour_species = list(neighbour_species)

if central_species is None:
central_species = []
elif not isinstance(central_species, list):
central_species = list(central_species)

self.update_hyperparameters(
max_radial=max_radial,
max_angular=max_angular,
expansion_by_species_method=expansion_by_species_method,
global_species=global_species,
central_species=central_species,
neighbour_species=neighbour_species,
compute_gradients=compute_gradients,
)
self.cutoff_function_parameters = deepcopy(cutoff_function_parameters)
Expand Down Expand Up @@ -258,6 +278,8 @@ def update_hyperparameters(self, **hypers):
"cutoff_function_parameters",
"expansion_by_species_method",
"global_species",
"central_species",
"neighbour_species",
}
hypers_clean = {key: hypers[key] for key in hypers if key in allowed_keys}
self.hypers.update(hypers_clean)
Expand Down Expand Up @@ -310,6 +332,8 @@ def _get_init_params(self):
max_angular=self.hypers["max_angular"],
expansion_by_species_method=self.hypers["expansion_by_species_method"],
global_species=self.hypers["global_species"],
central_species=self.hypers["central_species"],
neighbour_species=self.hypers["neighbour_species"],
compute_gradients=self.hypers["compute_gradients"],
gaussian_sigma_type=gaussian_density["type"],
gaussian_sigma_constant=gaussian_density["gaussian_sigma"]["value"],
Expand Down
Loading